With an automated data pipeline and a cloud-native database, an organization is well on its way toward a cloud-native data strategy. But moving the data and working with it in a cloud-native database won’t do the organization much good if employees can’t find the information they need. And it’s clear that finding information is a big problem in most organizations.
According to IDC, a typical data team spends four-fifths of its time on data discovery, preparation, and protection. That means out of an eight-hour day, just two hours is spent on generating insights. What’s more, 81% of employees have a hard time finding the information they need when they’re under the gun, according to a study from Wakefield Research and Elastic.
The ability to search data is a critical tool for accomplishing key business priorities. For example, 53% of organizations say they use search powered tools for cybersecurity, 52% for digital transformation initiatives, 50% for cloud migration and utilization, and 49% to improve the customer experience, according to a Forrester study.
“For all the zettabytes of data companies have amassed to date, surprisingly, little of it is actually being used efficiently,” said Brian Bergholm, senior marketing manager in the cloud product marketing team for Google Cloud technology partner Elastic. “In fact, most of the data winds up in silos of various kinds. So, when individuals are spending nearly half of their time simply gathering and organizing data, it means they have that much less time to actually analyze the data to derive insights.”
This inefficient approach to finding information has repercussions well beyond product development, marketing, and customer relationships. It also directly affects security. After all, in the Forrester study cited above, cybersecurity was the No. 1 use case for search-powered tools. With an integrated, cloud-based search platform, cybersecurity professionals can find the logs and other data they need to track down possible breaches and other threats. Additionally, the search platform itself must be secure.
“When organizations fall short of best practices and compliance measures for data privacy, like not sufficiently protecting sensitive information, the potential for negative impact on that organization or business has been made clear,” Bergholm said. “So, whether it be safeguarding medical information, or protecting customers' financial health, or defending governmental intelligence, or even just tackling information sharing in the manufacturing industry, the nuances of each sector require individual attention.”
Cloud-native search needs features such as role-based access control and strong data encryption to ensure that it is secure and compliant with data privacy regulations such as GDPR and CCPA.
For all the zettabytes of data companies have amassed to date, surprisingly, little of it is actually being used efficiently.
Elastic, a Google Cloud partner, provides a powerful, secure search platform that can find exactly the information one is looking for amid petabytes of data scattered across multiple data sources. And because it’s cloud-native, it scales automatically in the face of spikes. Retailers, for example, who are concerned about customers encountering a sluggish search for the gift they want around the holidays need not worry. Elastic takes full advantage of Google Cloud’s scalable infrastructure, along with high availability through cluster and geographic redundancy. And Elastic was designed with security and compliance in mind, providing powerful, granular access controls and strong encryption to protect data.
